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Bi-directional LSTM-CNNs-CRF for Italian Sequence Labeling

In this paper, we propose a Deep Learning architecture for sequence labeling based on a state of the art model that exploits both word- and character-level representations through the combination of bidirectional LSTM, CNN and CRF. We evaluate the proposed method on three Natural Language Processing...

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Detalhes bibliográficos
Principais autores: Basile, Pierpaolo, Semeraro, Giovanni, Cassotti, Pierluigi
Formato: Chapter
Idioma:Inglês
Publicado em: Accademia University Press 2017
Acesso em linha:https://doi.org/10.4000/books.aaccademia.2339
https://hdl.handle.net/20.500.13089/1d7i
https://books.openedition.org/aaccademia/2339
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